Publication: The traveling purchaser problem with fast service option
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Date
2022-01-21
Authors
Authors
Küçükoğlu, İlker
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
The traveling purchaser problem (TPP) is a generalization of the well-known traveling salesman problem, in which a list of products with different quantities has to be purchased from a subset of markets selling various products with different prices. The aim of the problem is to minimize total traveling and purchasing costs while satisfying the products demand in a unique tour. This study introduces a new variant of the TPP, in which the tour has to be completed within a duration time limit by taking into account the traveling and purchasing times of the purchaser. For the purchasing operations, two types of service options are allowed for the purchaser: standard and fast service. The fast service option of a market gives opportunities to the purchaser to complete the purchasing process in a shorter time with an additional cost. This problem is called the traveling purchaser problem with fast service option (TPP-FSO). In addition to presenting a new TPP variant to the literature, this paper proposes an adaptive large neighborhood search (ALNS) algorithm for the TPP-FSO. The proposed ALNS is enriched by a local search procedure, which consists of a set of route-change-based and procurement-changebased heuristics. To evaluate the performance of the ALNS on TPP-FSO, different-sized benchmark problems are generated by using a well-known TPP benchmark problem set. The results of the computations demonstrate the efficiency of the proposed algorithm by introducing better results in shorter computational times.
Description
Keywords
Large neighborhood search, Vehicle-routing problem, Cut algorithm, Formulation, Heuristics, Combinatorial optimization, Traveling purchaser problem, Meta-heuristics, Adaptive large neighborhood search, Science & technology, Technology, Computer science, interdisciplinary applications, Engineering, industrial, Operations research & management science, Computer science, Engineering, Operations research & management science